Munik Shrestha
Overview
Explore the profile of Munik Shrestha including associated specialties, affiliations and a list of published articles.
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Articles
6
Citations
215
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0
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Recent Articles
1.
Klein B, Hartle H, Shrestha M, Zenteno A, Barros Sierra Cordera D, Nicolas-Carlock J, et al.
PNAS Nexus
. 2024 Sep;
3(9):pgae306.
PMID: 39285936
During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced...
2.
Vespignani A, Tian H, Dye C, Lloyd-Smith J, Eggo R, Shrestha M, et al.
Nat Rev Phys
. 2021 Mar;
2(6):279-281.
PMID: 33728401
As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs...
3.
Rader B, Scarpino S, Nande A, Hill A, Adlam B, Reiner R, et al.
Nat Med
. 2020 Oct;
26(12):1829-1834.
PMID: 33020651
The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread. During the initial phase of the outbreak,...
4.
Bhat U, Shrestha M, Hebert-Dufresne L
Phys Rev E
. 2017 Feb;
95(1-1):012314.
PMID: 28208475
The giant k-core-maximal connected subgraph of a network where each node has at least k neighbors-is important in the study of phase transitions and in applications of network theory. Unlike...
5.
Shrestha M, Scarpino S, Moore C
Phys Rev E Stat Nonlin Soft Matter Phys
. 2015 Sep;
92(2):022821.
PMID: 26382468
Epidemic processes are common out-of-equilibrium phenomena of broad interdisciplinary interest. Recently, dynamic message-passing (DMP) has been proposed as an efficient algorithm for simulating epidemic models on networks, and in particular...
6.
Shrestha M, Moore C
Phys Rev E Stat Nonlin Soft Matter Phys
. 2014 Oct;
89(2):022805.
PMID: 25353532
We study a simple model of how social behaviors, like trends and opinions, propagate in networks where individuals adopt the trend when they are informed by threshold T neighbors who...